An Image Denoising Algorithm Based on Noise Detection
JIN LiangHai, LI DeHua
State Education Commission Key Laboratory for Image Processing and Intelligent Control, Institute for Pattern Recognition and Artificial Intelligence, Huazhong University of Science and Technology, Wuhan 430074
Abstract An efficient image denoising algorithm is introduced. Firstly, image pixels are classified into noisy pixels and noise-free pixels by four directional operators. Then an adaptive weighted median filter is designed to remove and restore the detected noisy pixels and keep the noise-free ones unchanged. Experimental results indicate that the proposed algorithm preserves image details well while removing impulsive noise efficiently, and its filtering performance is significantly superior to the classical median filter and some other typical and recently developed improved median filters.
[1] Abreu E, Lightstone M, Mitra S K, et al. A New Efficient Approach for the Removal of Impulse Noise from Highly Corrupted Images. IEEE Trans on Image Processing, 1996, 5(6): 1012-1025 [2] Tukey J W. Nonlinear (Nonsuperposable) Methods for Smoothing Data // Proc of the Electronics and Aerospace Systems Conference. Washington, USA, 1974: 673-681 [3] Ataman E, Aatre V K, Wong K M. Some Statistical Properties of Median Filters. IEEE Trans on Acoustics, Speech and Signal Processing, 1981, 29(5): 1073-1075 [4] Nodes T A, Jr Gallagher N C. Median Filters: Some Modifications and Their Properties. IEEE Trans on Acoustics, Speech and Signal Processing, 1982, 30(5): 739-746 [5] Yin Lin, Yang Ruikang, Gabbouj M, et al. Weighted Median Filters: A Tutorial. IEEE Trans on Circuits and Systems II: Analog and Digital Signal Processing, 1996, 43(3): 157-192 [6] Ko S J, Lee Y H. Center Weighted Median Filters and Their Applications to Image Enhancement. IEEE Trans on Circuits and Systems, 1991, 38(9): 984-993 [7] Yang P, Basir O A. Adaptive Weighted Median Filter Using Local Entropy for Ultrasonic Image Denoising // Proc of the 3rd International Symposium on Image and Signal Processing and Analysis. Rome, Italy, 2003, Ⅱ: 799-803 [8] Jin Lianghai, Li Dehua. Lu Zijian. Improved Adaptive Spatial Distance-Weighted Median Filter. Optical Engineering, 2007, 46(3): 037003-1-7 [9] Chen Tao, Ma Kaihuang, Chen Lihui. Tri-State Median Filter for Image Denoising. IEEE Trans on Image Processing, 1999, 8(12): 1834-1838 [10] Eng H L, Ma K K. Noise Adaptive Soft-Switching Median Filter. IEEE Trans on Image Processing, 2001, 10(2): 242-251 [11] Zhang D S, Kouri D J. Varying Weight Trimmed Mean Filter for the Restoration of Impulse Noise Corrupted Images // Proc of the IEEE International Conference on Acoustics, Speech and Signal Processing. Philadelphia, USA, 2005, Ⅳ: 137-140
2008, Vol. 21 
